城市影像地图集总体设计若干要点研究——以《广州市数字影像地图集》为例

城市影像地图集是一种基于遥感影像,以城市为空间表达对象的城市地图品种,本文结合《广州市数字影像地图集》的设计与生产,探讨了影像地图集不同于传统地图的特点和总体设计要点。     

关于现代城市影像地图集编制的探讨

城市影像地图集是一种基于航空影像和卫星遥感影像,以城市为空间表达对象的城市地图品种,本文以《乌海综合影像地图集》为例,探讨了现代影像地图集不同于以往影像地图集的特点和总体设计要点.     

基于卫星遥感影像的城市地图快速更新技术

实时，动态是当今科技发展的主要特点，更是测绘技术的基石，当前我国城市进入快速发展时期，如何实现城市地图的动态更新是我国地图工作者所面临的一个新课题。因此，提出了一种利用卫星遥感影像快速更新城市地图的技术方法，并用实硷证明采用这种方法的可行性。     

基于资源三号卫星影像的制图研究

资源三号卫星影像数据广泛应用于基础测绘、地理国情监测、地图数据更新等领域。本文运用资源三号影像进行地图制作研究。结果表明,资源三号卫星影像能用于城市道路和居民地的更新,可满足城市地图更新的需求。     

高分辨率遥感影像图制作的镶嵌线自动提取

为更好地发挥遥感技术在城市规划地图制作中的应用,高分辨率遥感影像成为城市地图制作中最重要的数据源。面对地物信息复杂、建筑物众多的城市地区,如何快速提取高分辨率遥感影像地图制作过程中相邻两景影像之间的镶嵌线具有重要意义。本文以国产卫星中分辨率最高、幅宽最小的GF-2影像为数据源,融合建筑物轮廓数据,研究了基于最短路径的A*搜索算法,实现了遥感影像地图制作的镶嵌线自动提取技术。结果表明,该方法能够自动生成避让建筑物的镶嵌线,速度快、镶嵌质量高,可广泛应用于城市地区高分辨率遥感影像地图制作。     

城市地图的内容和功能

城市地图是城市研究的可靠工具和城市研究成果的表达方式。现代城市的发展决定了城市研究内容的复杂性,也推动了城市地图的发展,使城市地图的内容丰富、图种增多、功能和作用不断扩大。在这种认识的基础上,本文提出按城市地图的内容分为城市普通地图和城市专题图,有助于提高对现代城市地图的认识。     

浅谈城市地图的表示方法

经济的快速发展促使城市面貌日新月异,出差、旅游、务工等活动成为大多数城市外来人口的主要选择,城市地图显得越来越重要,采用何种表示方法表达城市地图成为关键。本文以吉林市城市地图编制为依托,详细阐述了城市地图的表示方法,对编制城市地图的同仁具有一定的借鉴作用。     

影像城市·武汉

从思考网络电子地图如何满足城市空间信息服务的要求出发,分析了网络电子地图发展到可量测实景影像的发展历程,提出了网上影像城市的概念,并预见了影像城市将是网络电子地图的一场革命,介绍了影像城市·武汉的构建思路与架构及影像城市·武汉的特色,展望了影像城市的美好发展前景。     

结合高光谱和高空间分辨率影像提取城市固体废弃物堆

城市固体废弃物给城市的环境及居民的生活质量造成了严重的影响。利用遥感手段提取城市固废堆具有及时和高效的特点,因此具有十分重要的意义。然而,由于固废堆组成成分复杂、分布不规律,仅仅利用高分辨率影像进行提取十分困难。本文结合高光谱影像和高分辨率影像提取了城市固废堆,采用多尺度的研究方法,在对高光谱和高分辨率影像预处理的基础上,首先在高光谱影像上进行了粗提取,然后将粗略结果映射到高分辨率影像上,进行了精确提取。以北京市地区作为研究区域,使用数据包括获取时间接近的Quick Bird影像和Hyperion高光谱影像,利用提出的方法进行固废提取试验,并将最终的试验结果与目视判读结果进行对比,固废堆的识别率为82.35%,准确率为74.81%。同时,该方法与已有的固废提取试验对比结果有显著提高。这一结果表明,本文提出的结合高光谱影像和高分辨率影像提取城市固废堆方法具有可行性。     

“天地图”即将开通手机版和古地图频道

作为地理信息产业社会化应用的重要成果．公众版国家地理信息平台“天地图”建设日趋完善。记者近日从国家测绘地理信息局获悉．“天地图”将于近期开通手机版和古地图频道．并提供国外的城市地图和国内部分城市的街景影像、建筑物轮廓．三维模型等。     

Employing airborne multispectral digital imagery to map Brazilian pepper infestation in South Texas

A study was conducted in south Texas to determine the feasibility of using airborne multispectral digital imagery for differentiating the invasive plant Brazilian pepper (Schinus terebinthifolius) from other cover types. Imagery obtained in the visible, near-infrared, and mid-infrared regions of the light spectrum and a supervised classification approach were employed to develop thematic maps of two areas infested with Brazilian pepper. Map accuracies ranged from 84.2 to 100% for the Brazilian pepper class. Findings support using airborne multispectral digital imagery as a tool for separating Brazilian pepper from associated land cover types and further encourage exploration of airborne multispectral digital imagery and image processing techniques for developing maps of Brazilian pepper infestation in Texas and abroad.     

基于频域滤波的高分辨率遥感图像城市河道信息提取

提出一种基于频域滤波的城市河道信息提取方法。首先对高分辨率遥感图像进行傅里叶变换得到频谱图, 并利用径向和角向分布图分析城市河道的频谱特征。其次, 基于城市河道的双线型特点, 将其分为边缘特征和低频信息两个部分, 并根据周期性纹理的频谱模型和地物频谱能量分布规律确定两个部分的频域识别标志。然后设计相应的扇环形带通log Butterworth滤波器和低通Butterworth滤波器分别对城市河道的边缘特征和低频信息进行提取, 并根据该两部分信息实现城市河道信息提取。最后对城市河道信息提取结果进行定量评价, 结果表明, 本文方法可以有效地实现城市河道的信息提取。     

These lit areas are undeveloped: Delimiting China’s urban extents from thresholded nighttime light imagery

Nighttime light imagery is a powerful tool to study urbanization because it can provide a uniform metric, lit area, to delimit urban extents. However, lit area is much larger than actual urban area, so thresholds of digital number (DN) values are usually needed to reduce the lit area. The threshold varies greatly among different regions, but at present it is still not very clear what factors impact the changes of the threshold. In this study, urban extent by province for China is mapped using official statistical data and four intercalibrated and geometrically corrected nighttime light images between 2004 and 2010. Lit area in the imagery for most provinces is at least 94% greater than the official amount of urban area. Regression analyses show a significant correlation between optimal thresholds and GDP per capita, and larger thresholds more commonly indicate higher economic level. Size and environmental condition may explain a province’s threshold that is disproportionate to GDP. Findings indicate one threshold DN is not appropriate for multiple (adjacent) province urban extent mapping, and optimal thresholds for one year may be notably different than the next. Province-level derived thresholds are not appropriate for other geographic levels. Brightness of nighttime lights is an advantage over imagery that relies on daylight reflection, and decreases in brightness indicate faster growth in the horizontal direction than the vertical. A province’s optimal threshold does not always maintain an increase with population and economic growth. In the economically developed eastern provinces, urban population densities decreased (and this is seen in the brightness data), while urban population increased.     

Crop type mapping using LiDAR,Sentinel-2 and aerial imagery with machine learning algorithms

LiDAR data are becoming increasingly available, which has opened up many new applications. One such application is crop type mapping. Accurate crop type maps are critical for monitoring water use, estimating harvests and in precision agriculture. The traditional approach to obtaining maps of cultivated fields is by manually digitizing the fields from satellite or aerial imagery and then assigning crop type labels to each field - often informed by data collected during ground and aerial surveys. However, manual digitizing and labeling is time-consuming, expensive and subject to human error. Automated remote sensing methods is a cost-effective alternative, with machine learning gaining popularity for classifying crop types. This study evaluated the use of LiDAR data, Sentinel-2 imagery, aerial imagery and machine learning for differentiating five crop types in an intensively cultivated area. Different combinations of the three datasets were evaluated along with ten machine learning. The classification results were interpreted by comparing overall accuracies, kappa, standard deviation and f-score. It was found that LiDAR data successfully differentiated between different crop types, with XGBoost providing the highest overall accuracy of 87.8％. Furthermore, the crop type maps produced using the LiDAR data were in general agreement with those obtained by using Sentinel-2 data, with LiDAR obtaining a mean overall accuracy of 84.3％ and Sentinel-2 a mean overall accuracy of 83.6％. However, the combination of all three datasets proved to be the most effective at differentiating between the crop types, with RF providing the highest overall accuracy of 94.4％. These findings provide a foundation for selecting the appropriate combination of remotely sensed data sources and machine learning algorithms for operational crop type mapping.     

基于遥感影像的武汉市2003～2015年城区扩张及驱动力分析

以Landsat TM/OLI遥感影像为数据源,将武汉市土地利用分类情况主要分为建成区、植被、水体三类.通过统计对比2003～2015年的各类土地面积变化发现,武汉市建成区的面积呈逐年增加的趋势.结合分析各类统计数据得出影响武汉市城区扩张的驱动力因子中,地理环境、交通因素和人口因素为其扩张的基础条件,经济结构的转变是推动主城区向外扩张的内在动力,宏观规划政策的调控起着外在的引导作用.     

Utilizing the Potential of World View −2 for Discriminating Urban and Vegetation Features Using Object Based Classification Techniques

With the availability of very high resolution multispectral imagery, it is possible to identify small features in urban environment. Because of the multiscale feature and diverse composition of land cover types found within the urban environment, the production of accurate urban land cover maps from high resolution satellite imagery is a difficult task. This paper demonstrates the potential of 8 bands capability of World View 2 satellite for better automated feature extraction and discrimination studies. Multiresolution segmentation and object based classification techniques were then applied for discrimination of urban and vegetation features in a part of Dehradun, Uttarakhand, India. The study demonstrates that scale, colour, shape, compactness and smoothness have a significant influence on the quality of image objects achieved, which in turn governs the classified result. The object oriented analysis is a valid approach for analyzing high spatial and spectral resolution images. World View 2 imagery with its rich spatial and spectral information content has very high potential for discrimination of the less varied varieties of vegetation.     

Spatial-temporal impacts of urban land use land cover on land surface temperature: Case studies of two Canadian urban areas

The surface fabric of urbanized areas, (i.e. its constituent land covers and land uses) plays an essential role in the generation of the urban/rural temperature differences, i.e. the Urban Heat Island (UHI) effect. Land surface information, derived from satellite imagery, and complementary information such as demographics can be used as the basis for an understanding of the atmospheric and surface thermal variations within cities. The results of comprehensive land surface characterizations of two major Canadian urban areas, the Greater Toronto Area and Ottawa-Gatineau, are described. Spatial information, including land cover fraction maps, land use and its historic changes, population density maps are compared with intra-urban surface temperature variations derived from satellite thermal imagery. Three aspects of the impacts of land cover and land use on urban land thermal characteristics are addressed, namely, (a) the relationships between surface temperature and subpixel land cover and population density (b) intra-city seasonal temperature variations and (c) the intensification of the urban heat island effect due to urban built-up land growth.     

基于QuickBird遥感影像的棚户区提取与制图

以QuickBird遥感影像为数据源,从纹理信息的角度,利用灰度共生矩阵(GLCM)的方法对南京市下关区的棚户区信息进行了提取。首先,利用所选择的4个纹理特征统计量(对比度、能量、同质性和相关性)构建一个特征空间。然后运用非监督分类的方法(ISODATA算法)将研究区分成确定的类别数目。最后,根据实际情况,利用数学形态法对分类结果进行调整和优化,从而获得研究区域的棚户区信息。研究结果表明,基于纹理特征的灰度共生矩阵方法对于棚户区的提取和制图是有效可行的,同时本文的研究结果可以为南京市棚户区的管理及城市规划提供更为科学的依据。     

高分辨率卫星影像在1∶10000比例尺地形图(重要要素)更新与建库中的应用

通过GF-2号卫星影像在辽宁省1∶10 000比例尺地形图(重要要素)更新与建库的试生产,系统地阐述了项目的内容、方法、生产工艺和质量控制,验证了该方案的可行性,对保证项目的顺利进行具有重要意义。     

Automated mapping of impervious surfaces in urban and suburban areas: Linear spectral unmixing of high spatial resolution imagery

Quantifying impervious surfaces in urban and suburban areas is a key step toward a sustainable urban planning and management strategy. With the availability of fine-scale remote sensing imagery, automated mapping of impervious surfaces has attracted growing attention. However, the vast majority of existing studies have selected pixel-based and object-based methods for impervious surface mapping, with few adopting sub-pixel analysis of high spatial resolution imagery. This research makes use of a vegetation-bright impervious-dark impervious linear spectral mixture model to characterize urban and suburban surface components. A WorldView-3 image acquired on May 9th, 2015 is analyzed for its potential in automated unmixing of meaningful surface materials for two urban subsets and one suburban subset in Toronto, ON, Canada. Given the wide distribution of shadows in urban areas, the linear spectral unmixing is implemented in non-shadowed and shadowed areas separately for the two urban subsets. The results indicate that the accuracy of impervious surface mapping in suburban areas reaches up to 86.99%, much higher than the accuracies in urban areas (80.03% and 79.67%). Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component. To further extend the operational transferability of our proposed method, especially for the areas where plenty of bare soils exist during urbanization or reclamation, it is still of great necessity to mask out bare soils by automated classification prior to the implementation of linear spectral unmixing.